Rafal Kicinger Collection

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https://hdl.handle.net/1920/533

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Working together: Research & development partnerships in homeland security
(2005) Kicinger, Rafal P.
Critical Infrastructure Protection
(2005) Arciszewski, Tomasz; Kicinger, Rafal P.
Proactive security: From evolutionary approaches to cellular automata
(2005-04) Arciszewski, Tomasz; Kicinger, Rafal P.
The main objective of the paper is to propose several novel approaches to security of complex infrastructure systems, which can be utilized in the development of a class of computer tools for infrastructure protection. First, the paper introduces the concept of proactive infrastructure security and compares it with reactive security. The comparison is done in the context of the generation and evaluation of both the terrorist and security scenarios, which are also introduced and described. Next, the paper discusses both the evolutionary and co-evolutionary generation of terrorist and security scenarios and discusses various computer tools, which have been developed at George Mason University for infrastructure protection. Finally, the paper briefly overviews the concept of cellular automata and proposes how cellular automata could be used in the development of computer tools for infrastructure protection. The paper ends with the initial research conclusions and various suggestions for further research.
Conceptual Model of a Self-Organizing Traffic Management Hazard Response System
(2006-01) Bronzini, Michael; Kicinger, Rafal P.
The terrorist attacks of September 11, 2001 have sparked renewed interest in developing effective policies and strategies for evacuating densely populated areas. The current analytical tools for dealing with such evacuations are sorely lacking, in both theory and practice. The conceptual model presented in this paper marries the technical areas of cellular automata, evolutionary computation, and transportation science, along with some recent research on infrastructure security, to make significant progress in traffic management and hazard response systems. The overall goal of this research is to develop a fundamental understanding of the evolutionary and emergent behavior of transportation systems that are operating under emergency evacuation conditions. This new knowledge can be utilized to develop more effective operational strategies and consequently more robust hazard response systems. Furthermore, the specific research objective is to investigate the formulation and application of cellular automata models of metropolitan transportation systems, with a focus on systems operating under emergency evacuation conditions. The basic context is evacuation of a defined urban area, such as the urban core of Washington, DC under terrorist attacks. The conceptual model proposes the use of evolutionary algorithms to search the space of the evacuation control strategies and determine the most successful strategies for a given urban area.
Long term versus short term evolutionary design
(2002-08) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
Intelligent agent for designing steel skeleton structures of tall buildings
(2002-11) Skolicki, Zbigniew; Kicinger, Rafal P.
The paper discusses a study on the application of intelligent agents (IAs) to conceptual designing. It provides an overview of the state-of-the-art in the areas of ontologies and IAs. Next, the system Disciple, a learning intelligent agent shell, and the system Inventor 2001, evolutionary design support tool, both developed at George Mason University, are briefly presented. Further, the paper introduces the developed ontology for a class of steel skeleton structures of tall buildings. This ontology was used to build an IA for the selection of initial parent design concepts in evolutionary designing. A description of the developed agent is provided as well. Finally, examples of design concepts proposed by the agent are presented. The paper also contains conclusions and recommendations for further research.
George Mason University Intelligent Educator
(Millpress Science Publishers, 2003) Oguejiofor, Emeka; Kicinger, Rafal P.; Popovici, Elena; Arciszewski, Tomasz; De Jong, Kenneth A.
Engineering education is undergoing significant changes, mostly driven by the ongoing Information Technology Revolution. One of the most promising technologies becoming available to educators is that of intelligent software agents. Such agents can be used in building tutoring systems, which in this way become intelligent in terms of knowledge content, their ability to learn (acquire knowledge), and to adapt to the needs and learning preferences of their users. The paper discusses the development of a prototype intelligent tutoring system, called "George Mason University Intelligent Educator." It has been built as a result of a complex process in which various software development tools have been used in a novel way, including ConceptMap, Protégé2000, Macromedia Flash and JRun. The reported research is part of a NASA-sponsored project in the area of engineering education called "Hierarchical Learning Network" and is coordinated by the Old Dominion University in Virginia. The primary objective of the research at George Mason University is to develop a methodology for building intelligent tutoring systems and to demonstrate its feasibility. First, the paper provides a brief description of the process that was used for knowledge acquisition and its representation in the form of an ontology. The description includes examples from the area of personal air vehicles. Next, the development process for the proposed intelligent tutoring system is presented, along with a discussion of the integration of various software development tools. Finally, the initial research conclusions and plans for further research are discussed.
Conceptual design in structural engineering: An evolutionary computation approach
(2003-07) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
This paper describes a new design paradigm, evolutionary structural design, that involves the entire design process, including conceptual and detailed design stages. In this paper, first a brief overview of the fundamentals of evolutionary computation is provided. Next, the concept of evolutionary structural design and its principia are discussed. Inventor 2001 is described in the following section. It is an experimental research and design system based on evolutionary computation. The system has been developed by the authors at George Mason University for applications in the design of tall buildings. Inventor 2001 allows for the conducting of evolutionary structural design, including the generation of structural concepts and the detailed design, analysis of internal forces, dimensioning, and optimization. Selected specific research results are also provided, including a discussion of the discovered emergent structural shaping patterns that are surprisingly consistent with the state of the art in structural shaping of steel skeleton structures of tall buildings. Finally, the initial research conclusions are provided.
Proactive infrastructure security: Evolutionary generation of terrorist scenarios
(George Mason University Press, 2003) Arciszewski, Tomasz; De Jong, Kenneth A.; Sage, Andrew; Goode, Mike; Kicinger, Rafal P.; Skolicki, Zbigniew
The objectives of this working paper are to propose a general concept of proactive security in the context of co-evolutionary computation and to briefly discuss the initial results of research recently began. First, the paper provides an overview of infrastructure security in the context of asymmetric threats. Next, concepts of proactive security are proposed based on co-evolution of terrorist scenarios and security plans. The paper also presents an outline of generation of terrorist scenarios in the context of conceptual design. Finally, it describes TerrorMax/Capitol Hill, a demonstration system being developed for dealing with the generation of terrorist scenarios related to the Capitol Hill in Washington DC. The paper also provides initial discussions of this recently initiated project.
Distributed evolutionary design: Island-model based optimization of steel skeleton structures in tall buildings
(2004-06) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
This paper presents results of a study on distributed, or parallel, evolutionary computation in the topological design of steel structural systems in tall buildings. It describes results of extensive experimental research on various parallel evolutionary architectures applied to a complex structural design problem. The experiments were conducted using Inventor 2003, a network-based evolutionary design support tool developed at George Mason University. First, a general introduction to evolutionary computation is provided with an emphasis on recent developments in parallel evolutionary architectures. Next, a discussion of conceptual design of steel structural systems in tall buildings is presented. Further, Inventor 2003 is briefly introduced as well as its design representation and evolutionary computation characteristics. Next, the results obtained from systematic design experiments conducted with Inventor 2003 are discussed. The objective of these experiments was to qualitatively and quantitatively investigate evolution of steel structural systems in tall buildings during a distributed evolutionary design process as well as to compare efficiency and effectiveness of various parallel evolutionary architectures with the traditional evolutionary design approaches. Two connectivity topologies (ring topology and fully-connected topology) have been investigated for four populations of structural designs evolving in parallel and using various migration strategies. Also, results of the initial sensitivity studies are reported in which two ways of initializing distributed evolutionary design processes were investigated, using either arbitrarily selected designs as initial parents or randomly generated ones. Finally, initial research conclusions are presented.
Cellular automata in structural design
(Wolfram Media, 2004-04) Kicinger, Rafal P.
The goal of this project was to introduce NKS to engineering design problems and estimate a true potential of this approach. It was an initial step in exploring the world of simple programs for engineering design applications as well as introducing a novel methodology presented in Wolfram's A New Kind of Science. The motivation for this research was based on the fact that even designers of complex and sophisticated engineering systems (bridges, tall buildings, space structures, etc.) use only a relatively small set of design/decision rules to develop design concepts. Hence, it is plausible that even very complex designs of engineering systems can be modeled using simple programs like cellular automata (CA). Two potential ways of attacking this problem are based on the following observations. First, one of the important problems in engineering design is the problem of topological optimum design, where one seeks the optimal configuration of design elements satisfying some constraints, and optimizing a certain objective function, e.g. deflection, or weight, of a steel structure. This search for the optimal configuration of design elements sometimes yields very interesting patterns. It is possible that the search for such interesting structural patterns can be vastly enhanced using CA and other simple programs. Second, it is usually the case that engineering designs have repetitive forms. CA can generate both very simple and repetitive behavior as well as complex forms and configurations. It is definitely worth exploring whether the complex configurations of engineering systems will be better than traditional designs. The initial exploration of the space of simple programs has been focused on one-dimensional CA (1D CA) and two-dimensional CA (2D CA). 1D CA have been used to generate design concepts of wind bracing systems in tall buildings. These experiments were performed using both elementary CA where two possible types of bracings were used and more complex 1D CA involving 7 possible types of bracing elements. In another set of experiments 2D CA were used. Several types of totalistic 2D CA were studied, including Moore neighborhood and von Neumann neighborhood. The fitness of the generated design concepts was determined based on rigidity of the structural systems and measured by their maximum deflection. Results of the conducted experiments have shown that CA can generate interesting structural shaping patterns. They included both traditionally known patterns for this class of buildings like vertical and horizontal trusses, but also some novel arrangements of wind bracings characterized by high fitness values. The best results in the reported experiments were obtained using 1D CA. 2D CA also have the potential of producing interesting structural patterns but the search space is vastly larger compared to the 1D CA case and much larger number of experiments is necessary.
Morphogenesis and structural design: Cellular automata representations of steel structures in tall buildings
(IEEE Press, 2004-06) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
This paper provides the initial results of a study on the applications of generative cellular automata-based representations in evolutionary structural design. First, recent developments in evolutionary design representations and an overview of cellular automata are presented. Next, a complex problem of topological design of steel structural systems in tall buildings is briefly described. Further, morphogenic evolutionary design is introduced and exemplified by cellular automata representations. The paper also reports the initial results of several structural design experiments whose objective was to determine feasibility of the proposed approach. Finally, initial research conclusions are provided.
Emergent Designer: An integrated research and design support tool based on models of complex systems
(2004-07) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
The paper introduces an integrated research and design support tool, called Emergent Designer, developed at George Mason University. It is a tool that implements models of various complex systems, including cellular automata and evolutionary algorithms, to represent engineering systems and design processes. The system is intended for conducting design experiments in the area of structural design and for the analysis of their results. It implements state-of-the-art representations supporting generation of novel design concepts and efficient mechanisms for their subsequent optimization at the topology and sizing level. It also implements advanced methods, models, and tools from statistics and from the linear as well as nonlinear time series analysis to conduct the analysis of the design processes. Thus, it is a versatile tool that can be used both as a state-of-the-art design support tool and as an advanced research tool equipped with the methods and tools for the analysis of the design processes and of the obtained experimental results.
Multiobjective evolutionary design of steel structures in tall buildings
(American Institute of Aeronautics and Astronautics Press, 2004) Kicinger, Rafal P.; Arciszewski, Tomasz
This paper presents initial results of a study on the application of evolutionary multi-objective optimization methods in the design of the steel structural systems of tall buildings. In the paper, a brief overview of the state-of-the-art in evolutionary multi-objective optimization in structural engineering is provided. Next, conceptual design of steel structural systems in tall buildings is overviewed and the representations of steel structural systems used in the paper are discussed. Furthermore, Emergent Designer, a unique evolutionary design tool developed at George Mason University, is briefly described. It is an integrated research and design support tool which applies models of complex adaptive systems to represent engineering systems and to analyze design processes and their results. The paper also presents the results of several multi-objective structural design experiments conducted with Emergent Designer in which steel structural systems in tall buildings were optimized with respect to their total weight and maximum deflection (two-objective minimization problem). The goal of these experiments was to determine feasibility of evolutionary multi-objective optimization of steel structural systems of tall buildings as well as to qualitatively and quantitatively compare the results with the previous findings obtained with single-objective evolutionary optimization methods. Finally, initial research conclusions are presented as well as promising research directions.
Generative design in structural engineering
(American Society of Civil Engineers Press, 2005-07) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
This paper proposes a new approach to representing structural system inspired by various models of complex systems. Several types of generative representations of steel structural systems are provided and empirically investigated. These representations utilize various kinds of cellular automata to generate design concepts of steel structures in tall buildings. In the paper, a brief overview of the state-of-the-art in cellular automata and generative design is presented. Next, several types of generative representations of steel structural systems in tall buildings are described. The paper also reports the results of several design experiments. They have shown that generative representations produce novel structural shaping patterns which are qualitatively different than the patterns obtained using traditionally used parameterized representations. They also significantly improve the performance of evolutionary algorithms optimizing the structural systems. Finally, research conclusions are presented and most promising paths of future research are discussed.
Parameterized versus generative representations in structural design: An empirical comparison
(Association for Computing Machinery, http://www.acm.org/, 2005-06) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
Any computational approach to design, including the use of evolutionary algorithms, requires the transformation of the domain-specific knowledge into a formal design representation. This is a difficult and still not completely understood process. Its critical part is the choice of a type of design representation. The paper addresses this important issue by presenting and discussing results of a large number of design experiments in which parameterized and generative representations were used. Particularly, their computational and design related advantages and disadvantages were investigated and compared. Evolutionary design experiments reported in this paper considered two classes of structural design problems, including the design of a wind bracing system and the design of an entire structural system in a tall building. Parameterized and generative representations of the structural systems were introduced and their basic features discussed. The generative representations investigated in the paper were inspired by the processes of morphogenesis occurring in nature. Specifically, one-dimensional cellular automata were used to develop, or 'grow,' structural designs from the corresponding 'design embryos.' The conducted research led to three major conclusions. First, generative representations based on cellular automata proved to scale well with the size of the considered design problems. Second, generative representations outperformed parameterized representations in minimizing weight of the structural systems in our problem domain by generating better designs and finding them faster. Finally, extensive experimental studies showed significant differences in optimal settings for evolutionary design experiments for the two representation types. The rate of mutation operator, the size of the parent population, and the type of the evolutionary algorithm were identified as the evolutionary parameters having the largest impact on the performance of evolutionary design processes in our problem domain.
Intelligent tutoring systems: An ontology-based approach
(2004) Oguejiofor, Emeka; Kicinger, Rafal P.; Popovici, Elena; Arciszewski, Tomasz; De Jong, Kenneth A.
A novel methodology for building tutoring system is proposed. It includes the integration of state of the art computer science methods and tools and the use of an ontology for the core knowledge representation. First, the paper presents the ongoing Information Technology revolution in engineering and the related paradigm changes in education. Next, an overview of the concept of an ontology and its various definitions are provided, along with available ontology development tools. In the following section, an architecture of an ontology-based tutoring system is proposed. As a proof of concept, the proposed architecture has been used in GMU Educator, an intelligent tutoring system developed at George Mason University in the School of Information Technology and Engineering. A detailed description of the GMU Educator is then presented with various examples. Finally, conclusions and plans for further research are provided in the last section of the paper.
Evolutionary design of steel structures in tall buildings
(ASCE Research Library, http://ascelibrary.asce.org/, 2005) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
This paper presents results of a study on evolutionary computation in the design of the steel structural systems of tall buildings. It describes results of extensive research on both short-term (up to a few hundred generations) and long-term evolutionary design processes (at least a few thousand generations). The experiments were conducted with Inventor 2001, an evolutionary design support tool developed at George Mason University, for generating conceptual and detailed designs of steel structural systems in tall buildings. First, the paper discusses conceptual design of steel structural systems in tall buildings and briefly introduces Inventor 2001 as well as its design representation and evolutionary computation characteristics. Next, it provides the results obtained from systematic parametric design experiments conducted with Inventor 2001. The objective of these experiments was to qualitatively and quantitatively investigate evolution of steel structural systems of tall buildings during a multistage evolutionary design process as well as the influence of various evolutionary computation parameters. Mutation and crossover rates, population size, the length of the evolutionary processes, and the importance of symmetry requirement have been analyzed and results produced. Emergence of structural shaping patterns has been also studied and several interesting patterns found in the evolutionary design process. Finally, research conclusions are presented as well as recommendations for further research and development of evolutionary design support tools.
Evolutionary computation and structural design: A survey of the state of the art
(Elsevier, 2005-09) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
Evolutionary computation is emerging as a new engineering computational paradigm, which may significantly change the present structural design practice. For this reason, an extensive study of evolutionary computation in the context of structural design has been conducted in the Information Technology and Engineering School at George Mason University and its results are reported here. First, a general introduction to evolutionary computation is presented and recent developments in this field are briefly described. Next, the field of evolutionary design is introduced and its relevance to structural design is explained. Further, the issue of creativity/novelty is discussed and possible ways of achieving it during a structural design process are suggested. Current research progress in building engineering systems' representations, one of the key issues in evolutionary design, is subsequently discussed. Next, recent developments in constraint-handling methods in evolutionary optimization are reported. Further, the rapidly growing field of evolutionary multiobjective optimization is presented and briefly described. An emerging subfield of coevolutionary design is subsequently introduced and its current advancements reported. Next, a comprehensive review of the applications of evolutionary computation in structural design is provided and chronologically classified. Finally, a summary of the current research status and a discussion on the most promising paths of future research are also presented.
Emergent Designer: An integrated research and design support tool based on models of complex systems
(International Journal of Information Technology in Construction, http://www.itcon.org/, 2005) Kicinger, Rafal P.; Arciszewski, Tomasz; De Jong, Kenneth A.
This paper introduces an integrated research and design support tool, called Emergent Designer, developed at George Mason University. It is a tool that implements models of various complex systems, including cellular automata and evolutionary algorithms, to represent engineering systems and their related design processes. The system is intended for conducting design experiments in the area of structural design and for the analysis of their results. It implements state-of-the-art representations supporting generation of novel design concepts and efficient mechanisms for their subsequent optimization at the topological and sizing levels. The first part of this paper describes the overall system's architecture and the flow of information among its components. The actual system's implementation is discussed next and illustrated with several screen shots of the system's graphical user interface. Emergent Designer's novel approach to representing steel structural systems in tall buildings is also presented. It is based on the use of generative representations which utilize cellular automata to generate design concepts. Several design experiments are briefly described to demonstrate the feasibility of Emergent Designer in conceptual design as well as of design processes modeled by complex systems.

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